The group of Prof. Rasulev is focused on development of Artificial Intelligence (AI)-based predictive models to design novel polymeric materials, nanomaterials and predict their various properties, including toxicity, solubility, fouling release properties, elasticity, Tg, degradation rate, biodegradation, anti-ice properties, etc. The group applies computational chemistry, machine learning (ML) and cheminformatics methods for modeling, data analysis and development of predictive structure-property relationship models to find structural factors responsible for activity of investigated materials. The group also develops web applets that make available developed AI/ML models to public, where scientists can predict various properties for the organic chemicals and polymeric materials of their interest.
The head of the group, Prof. Bakhtiyor Rasulev is a Professor at Department of Coatings and Polymeric Materials (CPM); and also the Affiliate faculty in Materials and Nanotechnology (MNT) Program and Biomedical Engineering (BME) Program at NDSU.
The Rasulev group is also involved in development of methods to investigate complex materials (multi-component materials, multi-layered materials, nanomaterials, additives, cross-linked polymeric materials) by artificial intelligence (AI) and machine learning (ML) methods and predict various materials properties. The group constantly generates new data and develops a materials database, which can be applied to design new polymeric materials, nanomaterials and hybrid/composite materials, as well as to help in prediction of various physico-chemical properties, biological activity, including toxicity and degradation pathways for life cycle assessment.
